This disclosure relates generally to medical diagnostic imaging methods and systems, and more particularly to medical diagnostic imaging methods and systems that acquire and process tissue information for measuring the visceral fat mass of an individual.
Characteristics of an individual, such as body weight, fat mass, height, gender, age, etc. are clinical descriptors useful by physicians to predict certain health risks that may increase or decrease mortality and morbidity risk. For example, the amount or type of abdominal fat, such as subcutaneous adipose tissue (SAT) or subcutaneous fat and visceral adipose tissue (VAT) or visceral fat are associated with, and useful predictors of, an adverse metabolic risk profile and certain diseases, such as coronary heart disease and diabetes. In addition, measuring visceral fat, for example, can relate to metabolic syndrome (i.e., a combination of medical problems that can increase the risk of heart disease and/or diabetes). People suffering from metabolic syndrome can have some or all of the following: high blood glucose, high blood pressure, abdominal obesity, low high-density lipoprotein (HDL) cholesterol, high low-density lipoprotein (LDL) cholesterol, high total cholesterol and/or high triglycerides.
Conventional methods and systems for measuring VAT are mostly performed using anthropomorphic gauges, bioimpedance gauges, weight scales, etc. These devices often are not capable of providing accurate measurements of VAT because the actual fat content is not being measured, certain assumptions/estimates are made during the calculation process, and/or the devices are not exactly calibrated. Also, reproducibility may be difficult, leading to inaccurate comparisons between examinations.
Medical diagnostic imaging systems have also been used to measure VAT content. However, the use of these systems are often costly and can expose a patient to high levels of ionizing radiation, for example, when using a computed tomography (CT) imaging system. Additionally, these imaging systems are not always available for clinical use and may have long scan times. Moreover, certain measurements are inaccurate in larger individuals.
Conventional methods and systems for determining VAT often also use simple models to approximate the abdominal cavity from an estimate of subcutaneous fat thickness measurements. However, these methods and systems often fail to accurately estimate SAT, thereby resulting in an inaccurate estimate of VAT. For example, a normal dual-energy X-ray absorptiometry (DXA) image of the abdomen is a planar two-dimensional (2D) image that cannot explicitly measure VAT because it cannot measure the thickness of SAT in the vertical plane. It has been very difficult to determine the thickness of the subcutaneous fat layer around the abdomen, especially near the buttocks, since the models used in the past do not take into account differences in the thickness of the subcutaneous fat layer around the abdomen near the buttocks.
Therefore, there is a need for a method and system to more accurately measure VAT using DXA by measuring and correcting for SAT composition.